CONF
hung:MM:2007/IDIAP
Using Audio and Video Features to Classify the Most Dominant Person in a Group Meeting
Hung, Hayley
Jayagopi, Dinesh Babu
Yeo, Chuohao
Friedland, Gerald
Ba, Silèye O.
Odobez, Jean-Marc
Ramchandran, Kannan
Mirghafori, Nikki
Gatica-Perez, Daniel
EXTERNAL
https://publications.idiap.ch/attachments/papers/2007/hung-MM-2007.pdf
PUBLIC
https://publications.idiap.ch/index.php/publications/showcite/hung:rr07-29
Related documents
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2007
IDIAP-RR 07-29
The automated extraction of semantically meaningful information from multi-modal data is becoming increasingly necessary due to the escalation of captured data for archival. A novel area of multi-modal data labelling, which has received relatively little attention, is the automatic estimation of the most dominant person in a group meeting. In this paper, we provide a framework for detecting dominance in group meetings using different audio and video cues. We show that by using a simple model for dominance estimation we can obtain promising results.
REPORT
hung:rr07-29/IDIAP
Using Audio and Video Features to Classify the Most Dominant Person in a Group Meeting
Hung, Hayley
Jayagopi, Dinesh Babu
Yeo, Chuohao
Friedland, Gerald
Ba, Silèye O.
Odobez, Jean-Marc
Ramchandran, Kannan
Mirghafori, Nikki
Gatica-Perez, Daniel
EXTERNAL
https://publications.idiap.ch/attachments/reports/2007/hung-idiap-rr-07-29.pdf
PUBLIC
Idiap-RR-29-2007
2007
IDIAP
To appear in Association for Computing Machinery - Multimedia (ACM-MM,',','),
September 23--28, 2007, Augsburg, Bavaria, Germany.
The automated extraction of semantically meaningful information from multi-modal data is becoming increasingly necessary due to the escalation of captured data for archival. A novel area of multi-modal data labelling, which has received relatively little attention, is the automatic estimation of the most dominant person in a group meeting. In this paper, we provide a framework for detecting dominance in group meetings using different audio and video cues. We show that by using a simple model for dominance estimation we can obtain promising results.